The Role of Gender in Students' Academic Achievement: An Appraisal of COBEKS Artificial Intelligence Model, Simulation Games Model and Conventional Lecture Model

Authors

  • Obeka Caleb Department of Computer Science, Wesley University, Ondo

DOI:

https://doi.org/10.55366/suse.v3i3.30

Keywords:

Artificial Intelligence, COBEKS Artificial Intelligence Model, Gender, Simulation Game Model (SGM), Academic Achievement

Abstract

This quasi-experimental study investigated the influence of gender on students' academic achievement across three instructional models: conventional lectures, the COBEKS Artificial Intelligence Model (CAI), and the Simulation Games Model (SGM). A non-equivalent group design involved 500 SS2 students from four schools, assigned to experimental (CAI, SGM) and control groups. Instruments included the COBEKS Achievement Test (CAT, r=0.92) and the Challenges and Prospects Inventory Questionnaire (CPIQ, r=0.79). Five 45-minute intervention sessions covered AI, SGM, and contemporary topics. Data analysis used means, standard deviations, and effect size calculations. Findings unequivocally show that gender significantly influences academic achievement when students are taught using CAI and SGM, rejecting the null hypothesis. This aligns with recent scholarship on gender disparities in technology-enhanced learning (Kalim et al., 2025; Fadillah & Akbar, 2025), noting CAI's adaptive learning and personalised feedback likely contributed to its differentiated impact. While initial gender differences in AI literacy exist, targeted courses can mitigate them. We conclude that gender is a potent factor in academic attainment across varied instructional models. Recommendations, in line with the UNESCO 2024 "Women for Ethical AI" study, include adopting gender-sensitive approaches, targeted educator training, and inclusively designed instructional materials and AI models.

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Published

2026-01-28

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